🛠 Tech Stack

💼 About This Role

You'll lead the technical charge to scale and productionize core ML capabilities at PrizePicks. You'll design and build end-to-end ML infrastructure, transitioning experimental models into high-availability production services. This role directly impacts key metrics like Time-to-Bet and Deposit Velocity across our sports betting ecosystem.

🎯 What You'll Do

• Design and build end-to-end machine learning infrastructure for production services.
• Deploy low-latency inference services for real-time decisions like oddsmaking and risk analysis.
• Partner with Data Science to build scalable logging and feature data pipelines.
• Champion MLOps best practices for model deployment, monitoring, and CI/CD.

📋 Requirements

• 7+ years in Machine Learning Engineering or Backend Engineering with production ML.
• 3+ years of technical leadership driving architecture decisions.
• Experience with real-time data (Kafka/Flink/PubSub) and sub-100ms inference.
• Expert in Python and SQL; proficiency in Go, C++, or Rust is a plus.

✨ Nice to Have

• Experience implementing reinforcement learning or probabilistic models for pricing/risk.
• Background in Daily Fantasy Sports, oddsmaking, or high-frequency trading.
• Experience building and scaling Feature Stores for batch and real-time data.

🎁 Benefits & Perks

• 🏥 Company-subsidized medical, dental, vision plans
• 💰 Annual bonus and 401(k) with company match
• 🏖️ Flexible PTO with 2 weeks strongly encouraged
• 👶 16-week paid parental leave and disability benefits
• 💻 Workplace flexibility and company equipment provided

📨 Hiring Process

Estimated timeline: 2-4 weeks · AI estimate

1. 1Recruiter Screen· 30 min
2. 2Technical Interview· 60 min
3. 3System Design Interview· 60 min
4. 4Hiring Manager Interview· 45 min